Method and apparatus for detecting open flame, and storage medium

ABSTRACT

A method for detecting an open flame includes: acquiring a plurality of frames of first images of a suspected target in a monitoring region; acquiring gray scale change features of the plurality of frames of first images and attribute features of the suspected target based on the plurality of frames of first images, the gray scale change features being configured to indicate temperature changes of the suspected target; and determining the suspected target in the monitoring region as an open flame, if the gray scale change features of the plurality of frames of first images and the attribute features of the suspected target both satisfy an open flame condition.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a US national phase application of internationalapplication No. PCT/CN2019/128864, filed on Dec. 26, 2019, which claimspriority to the Chinese Patent Application No. 201910059674.1, filed onJan. 22, 2019 and titled “METHOD AND APPARATUS FOR DETECTING OPEN FLAME,AND STORAGE MEDIUM”, the disclosure of each of which is hereinincorporated by reference in its entirety.

TECHNICAL FIELD

The present disclosure relates to the field of safety protection, inparticular to a method and apparatus for detecting an open flame, and astorage medium.

BACKGROUND

Public places, factories, etc. all have non-smoking areas. Smoking innon-smoking areas not only affects the human health, but also posessafety risks. Therefore, it is necessary to detect an open flame causedby smoking in the non-smoking areas.

SUMMARY

According to an aspect, an embodiment of the present disclosure providesa method for detecting an open flame. The method includes:

acquiring a plurality of frames of first images of a suspected target ina monitoring region;

acquiring gray scale change features of the plurality of frames of firstimages and attribute features of the suspected target based on theplurality of frames of first images, the gray scale change featuresbeing configured to indicate temperature changes of the suspectedtarget; and

determining the suspected target in the monitoring region as an openflame if the gray scale change features of the plurality of frames offirst images and the attribute features of the suspected target bothsatisfy an open flame condition.

According to another aspect, an embodiment of the present disclosureprovides an apparatus for detecting an open flame. The apparatusincludes:

a first acquiring module, configured to acquire a plurality of frames offirst images of a suspected target in a monitoring region;

a second acquiring module, configured to acquire gray scale changefeatures of the plurality of frames of first images and attributefeatures of the suspected target based on the plurality of frames offirst images, the gray scale change features being configured toindicate temperature changes of the suspected target; and

a first determining module, configured to determine the suspected targetin the monitoring region as an open flame, if the gray scale changefeatures of the plurality of frames of first images and the attributefeatures of the suspected target both satisfy an open flame condition.

According to another aspect, an embodiment of the present disclosureprovides an apparatus for detecting an open flame, including a processorand a memory, wherein the memory stores at least one instructiontherein, the instruction being loaded and performed by the processor toimplement any of the methods for detecting the open flame as mentionedabove.

According to another aspect, an embodiment of the present disclosureprovides a computer-readable storage medium storing at least oneinstruction therein, the instruction being loaded and performed by theprocessor to implement any of the methods for detecting the open flameas mentioned above.

BRIEF DESCRIPTION OF THE DRAWINGS

To describe the technical solutions in the embodiments of the presentdisclosure more clearly, the following briefly introduces theaccompanying drawings required for describing the embodiments.Apparently, the accompanying drawings in the following description showmerely some embodiments of the present disclosure, and a person ofordinary skill in the art may still derive other drawings from theseaccompanying drawings without creative efforts.

FIG. 1 is a schematic diagram of an implementing environment accordingto an embodiment of the present disclosure;

FIG. 2 is a flowchart of a method for detecting an open flame accordingto an embodiment of the present disclosure;

FIG. 3 is a schematic structural diagram of an apparatus for detectingan open flame according to an embodiment of the present disclosure;

FIG. 4 is a schematic structural diagram of a second acquiring moduleaccording to an embodiment of the present disclosure;

FIG. 5 is a schematic structural diagram of a first acquiring moduleaccording to an embodiment of the present disclosure.

FIG. 6 is a schematic structural diagram of a fourth acquiring unitaccording to an embodiment of the present disclosure;

FIG. 7 is a schematic structural diagram of an apparatus for detectingan open flame according to an embodiment of the present disclosure; and

FIG. 8 is a schematic structural diagram of a terminal according to anembodiment of the present disclosure.

DETAILED DESCRIPTION

Unless otherwise defined, all terms used in embodiments of the presentdisclosure have the same meaning as commonly understood by a person ofordinary skill in the art. In order to make the objectives, technicalsolutions and advantages of the present disclosure clearer, a furtherdetailed description will be made to the embodiments of the presentdisclosure below with reference to the accompanying drawings.

The related art provides a method for detecting an open flame. Themethod includes: acquiring images of a suspected target in a monitoringregion; acquiring some features, such as, an area of the suspectedtarget, a shape of the suspected target and whether the suspected targetis dynamic based on the images of the suspected target; and determiningthat the suspected target in the monitoring region is an open flame ifthese features meet an open flame condition.

When the features (an area, a shape, and whether being dynamic) all meetthe open flame condition, the suspected target is not necessarily anopen flame, which makes the detection accuracy of this method low.

Open flames caused by smoking in non-smoking areas not only affect thehuman health, but may also cause explosions and other accidents and posesafety hazards. Therefore, warning signs such as “No smoking”, “No openflames” and “Open flames prohibited” are provided in the no-smokingareas. However, some people ignore these warning signs and engage insmoking and other behaviors to cause open flames, which affects thehuman health and safety. Therefore, it is necessary to detect openflames in the no-smoking areas. In this case, embodiments of the presentdisclosure provide a method and apparatus for detecting an open flame,and a storage medium.

FIG. 1 is a schematic diagram of an implementing environment accordingto an example embodiment. The implementing environment includes at leastone terminal 11 and a photographing apparatus 12. The photographingapparatus 12 may be directly fixed on the terminal 11; or thephotographing apparatus 12 may also be provided separately and not fixedto the terminal 11. As shown in FIG. 1, a description is made by takingthe photographing apparatus 12 being connected to the terminal 11electrically or wirelessly as an example. The terminal 11 acquires aplurality of frames of images of a monitoring region through thephotographing apparatus 12.

The terminal 11 may be any electronic product that may perform aman-machine interaction with a user through one or more means such as akeyboard, a touch panel, a touch screen, a remote controller, voiceinteraction, or a handwriting device. For example, the terminal 11 maybe a personal computer (PC), a mobile phone, a smart phone, a personaldigital assistant (PDA), a wearable device, a pocket PC (PPC), a tabletcomputer, a smart vehicle-mounted machine, a smart TV, or a smartspeaker.

The photographing apparatus 12 is a device with a function of acquiringimages or videos, which may be, for example, an infrared camera or aninfrared vidicon.

A person skilled in the art should understand that the aforementionedterminal 11 and photographing apparatus 12 are only examples. Otherterminals or servers that may appear at present or in the future areapplicable to the present disclosure, and should also be included in theprotection scope of the present disclosure, which are incorporatedherein by reference in their entireties.

Based on the implementing environment, a method for detecting an openflame according to an embodiment of the present disclosure will bedescribed in detail below in conjunction with the accompanying drawings.

FIG. 2 is a flowchart of a method for detecting an open flame accordingto an embodiment as an example. This method is applied to an electronicdevice, such as the terminal 11 shown in FIG. 1. Referring to FIG. 2,the method includes the following steps.

In step 21, a plurality of frames of first images of a suspected targetin a monitoring region is acquired.

Optionally, the step 21 includes, but is not limited to the followingsub-steps.

In sub-step 211, a plurality of frames of second images in themonitoring region is acquired, wherein a region displayed by the secondimages includes a region displayed by the first images.

In the embodiment of the present disclosure, this method being appliedto the terminal shown in FIG. 1 is taken as an example. The terminal mayacquire the plurality of frames of second images in the monitoringregion through a photographing apparatus. If there is a suspected targetthat may be an open flame in the monitoring region, the suspected targetcan be displayed in the second images. Taking the images including thesuspected target being the first images as an example, since thesuspected target is located in the monitoring region, a region occupiedby the suspected target is smaller than that of the monitoring region,and the region displayed by the second images in the monitoring regionincludes the region displayed by the first images. That is, the regiondisplayed by the first images is smaller than the region displayed bythe second images. Then, the second images in the monitoring region maybe acquired before the first images of the suspected target in themonitoring region are acquired.

For example, the terminal may directly acquire a plurality of frames ofsecond images in the monitoring region. For example, the terminal maydirectly acquire a plurality of frames of second images in themonitoring region through the photographing apparatus. For example, theterminal may also detect a temperature in the monitoring region througha temperature detecting apparatus prior to acquiring the plurality offrames of second images in the monitoring region. If there is a regionin which a temperature is higher than a temperature threshold in themonitoring region, the terminal acquires the plurality of frames ofsecond images in the monitoring region. If the temperature in themonitoring region is lower than the temperature threshold, the terminaldoes not acquire the plurality of frames of second images in themonitoring region.

It should be noted that in this method, the plurality of frames ofsecond images form continuous images, that is, a video. Datacorresponding to the plurality of frames of second images acquired bythe terminal may be referred to as raw data. When the terminal processesthe plurality of frames of second images, it essentially processes theraw data.

When the photographing apparatus is the infrared camera, the raw dataacquired by the terminal is raw data for thermal imaging. The terminalmay convert the raw data for thermal imaging into 8-bit image data andfull-screen temperature measuring data. The terminal may acquire pixelsof an image based on the 8-bit image data, and acquire gray scales ortemperatures corresponding to different areas in the image based on thefull-screen temperature measuring data.

The temperature detecting apparatus may be in signal connection to theterminal or directly fixed on the terminal. The temperature detectingapparatus may be a multi-light radiation thermometer, a digitalthermometer, or the like.

In step 212, images of a suspected region are acquired by extracting aregion having a gray scale value greater than a gray scale thresholdfrom each frame of second image, wherein the suspected target is locatedin the suspected region.

A temperature of an open flame is different from that of its surroundingregion, and a gray scale corresponding to an open flame image isdifferent from that of its surrounding region, and a change in grayscale can indicate a change in temperature. For example, when the secondimages include a region having a gray scale value greater than the grayscale threshold, this region having the gray scale value greater thanthe gray scale threshold may be regarded as a suspected region, i.e., aregion where an open flame may occur. In this case, the terminal maysegment the images of the suspected region from the second images bymeans of a gray scale threshold segmenting method or a temperaturethreshold segmenting method.

Taking smoking as an example, a lit cigarette butt has a highertemperature than its surrounding region. Images of a suspected regionhaving a temperature greater than 100° C. are acquired by extracting thesuspected region from each frame of second image, and the lit cigarettebutt is located in this suspected region.

In step 213, the plurality of frames of first images are acquired byextracting the images of the suspected target from the plurality offrames of images of the suspected region.

Optionally, with respect to the case where a plurality of suspectedtargets are located in the images of the suspected region, the step 213includes, but is not limited to the following sub-steps.

In sub-step 2131, distances between each suspected target and othersuspected targets in the images of the suspected region is respectivelyacquired.

For example, that the data corresponding to the plurality of frames ofsecond images acquired by the terminal is regarded as raw data forthermal imaging, the terminal converts the raw data for thermal imaginginto 8-bit image data and the terminal may acquire pixels of an imagebased on the 8-bit image data is still taken as examples, afteracquiring the plurality of frames of first images, the terminal acquirespixels of each suspected target by processing the 8-bit image data ofeach frame of image of the suspected region. Each pixel hascorresponding coordinates, and the terminal may determine a distancebetween each suspected target and other suspected targets based on thecoordinates of the pixel.

Since there may be a plurality of pixels for each suspected target, theterminal may determine a position of the suspected target by selecting amiddle pixel or a boundary pixel, which is not limited in the embodimentof the present disclosure. The position of each suspected target may bedetermined in the same way.

In sub-step 2132, distance ranges between each open flame and other openflames in the open flame image are acquired.

The open flame image may be a reference image configured to provide adistance range between the open flames. The distance range may bedirectly stored in the terminal, or the terminal may also collect andacquire this distance range from other devices.

In sub-step 2133, the plurality of frames of first images may beacquired by segmenting a region of the suspected target from each frameof image of the suspected region, if each distance between the suspectedtarget and other suspected target in the image of the suspected regionis within the distance range.

For example, if a distance between the suspected target and othersuspected target is detected as 3 meters, and the distance between a litcigarette butt and other lit cigarette butt ranges from 0.2 meter to 50meters, it is necessary to segment this suspected target from the imagesof the suspected region to acquire the first images.

The region of the suspected target may be segmented from the images ofthe suspected region by a masking method, so as to acquire the pluralityof frames of first images.

A suspected target to be determined is screened by means of the abovemethod, such that the suspected target can be accurately determined,which is beneficial to improve an accuracy of the method for detectingthe open flame.

Optionally, the step 213 further includes the following sub-steps.

In sub-step 2134, at least one of a position of the suspected target anda number of pixels of the suspected target in each image of thesuspected region is acquired; a pixel number range of the open flame anda position range of the open flame in the open flame image are acquired;and the plurality of frames of first images are acquired by segmenting aregion of the suspected target from each frame of image of the suspectedregion, if the suspected target in the image of the suspected regionsatisfies at least one of the followings: the position of the suspectedtarget is within the above-mentioned position range and the number ofpixels of the suspected target is within the above-mentioned pixelnumber range.

In addition, the sub-step 2134 may also be combined with the sub-step2131 to the sub-step 2133. If any one of the above three features of theimage of the suspected region correspondingly satisfies any one of theabove three features of the open flame image, the region of thesuspected target is segmented from each frame of image of the suspectedregion, so as to acquire the plurality of frames of first images.

In step 22, gray scale change features of the plurality of frames offirst images and attribute features of the suspected target are acquiredbased on the plurality of frames of first images, the gray scale changefeatures being configured to indicate temperature changes of thesuspected target.

The gray scale change features of the plurality of frames of the firstimage include at least one of change features of gray scales of theplurality of frames of first images in a time domain and change featuresof gray scales of the plurality of frames of first images in a frequencydomain. The attribute features of the suspected target include at leastone of the followings: an area of the suspected target, a shape of thesuspected target, a time that the suspected target stays at the sameposition, and whether the suspected target is dynamic.

Optionally, when the gray scale change features of the plurality offrames of first images include change features of the gray scales of theplurality of frames of first images in the time domain. In step 22, saidacquiring the gray scale change features of the plurality of frames offirst images based on the plurality of frames of first images includes,but is not limited to the following sub-steps.

In sub-step 221, a gray scale and time of each frame of first image areacquired.

The terminal acquires the gray scale of each frame of first image byprocessing the raw data corresponding to each frame of first image. Theterminal may acquire the time corresponding to each frame of first imageby timing, when acquiring each frame of first image. Taking the terminalacquiring the first images through the photographing apparatus as anexample, the terminal times when acquiring each frame of first image.This timing may refer to timing a time at which the photographingapparatus acquires a first image. For example, if the photographingapparatus captures the first image at 10:10:00, the time correspondingto the first image is 10:10:00.

It may be understood that the plurality of frames of first images form avideo of the suspected target. If an interval time between each frame offirst image is t and the time of the first frame of first image isrecorded as 0, the time corresponding to the plurality of frames offirst images may be 0, t, 2t, and so on.

In sub-step 222, change features of gray scales of the plurality offrames of first images in the time domain are acquired based on the grayscale and time of each frame of first image.

The change features of the gray scales of the plurality of frames offirst images in the time domain may be a change curve of the gray scalesin the time domain. For example, a graph is drawn by taking the timecorresponding to each frame of first image as an abscissa and the grayscale of each frame of first image as an ordinate, thereby acquiring achange curve of the gray scale in the time domain.

Optionally, the gray scale change features of the plurality of frames offirst images include change features of gray scales of the plurality offrames of first images in a frequency domain. In step 22, said acquiringthe gray scale change features of the plurality of frames of firstimages based on the plurality of frames of first images includes, but isnot limited to the following sub-steps.

In sub-step 22 a, a gray scale of each frame of first image is acquired.

In sub-step 22 b, change features of the plurality of frames of firstimages in the frequency domain are acquired by transforming the grayscale of each frame of first image to the frequency domain by means of aFourier transform formula.

It should be noted that the sub-step 22 b includes: at least two framesof first images having the same gray scale based on the gray scale ofeach frame of first image are respectively acquired, the at least twoframes of first images are sorted into a chronological order and thenthe gray scale of each frame of first image is transformed to thefrequency domain by means of the Fourier transform formula.

The change features of the gray scales of the plurality of frames offirst images in the frequency domain may be a change curve of the grayscales in the frequency domain. For example, the change features of thegray scales of the first images in the frequency domain are establishedby taking frequencies that gray scale values of the first images appearas an abscissa, and amplitude values of the gray scales of the firstimages in the frequency domain as an ordinate. Alternatively, the changefeatures of the gray scales of the first images in the frequency domainare established by taking the gray scale values of the first images asan abscissa, and a number of the gray scales of the first images whoseamplitude values in the frequency domain are greater than a referencethreshold as an ordinate.

Optionally, the attribute features of the suspected target include thetime that the suspected target stays at the same position. In the step22, said acquiring the attribute features of the suspected target basedon the plurality of frames of first images includes, but is not limitedto the following sub-steps.

In step 22A, a position of the suspected target in each frame of firstimage is determined.

The terminal acquires pixels of each frame of first image and acquirethe position of the suspected target in each frame of first image basedon coordinates of each pixel.

Each frame of first image may include a plurality of pixels. In a casethat the position of the suspected target in the first images isdetermined, a position of a middle pixel or a boundary pixel of eachfirst image may be determined as the position of the suspected target inthe first image.

In sub-step 22B, at least two frames of first images in which thesuspected target has a same position, and an interval time between twoadjacent frames of first images are acquired.

In sub-step 22C, a time that the suspected target stays at the sameposition is acquired by accumulating the interval time between twoadjacent frames of first image among the at least two frames of firstimages.

For example, if an interval time between two adjacent frames of firstimages is t, and a number of frames of first images at the same positionis 6, the interval time between these 6 frames of first images is 5t.

Optionally, the attribute features of the suspected target includedetermining whether the suspected target is dynamic. In step 22, saidacquiring the attribute features of the suspected target includes, butis not limited to the following sub-steps.

In sub-step I, pixels of each frame of first image are acquired.

In sub-step II, a position of the suspected target in each frame offirst image is determined based on the pixels of each frame of firstimage.

In sub-step III, the suspected target is determined to be dynamic if thepositions of the suspected target in at least two frames of first imagesare different.

After the position of the suspected target in each frame of first imageis determined, if the positions of the suspected target in at least twoframes of first images are different, it means that the suspected targethas moved, and thus the suspected target may be determined to bedynamic. If the position of the suspected target in each frame of firstimage is the same, it means that the suspected target does not move.

Optionally, the attribute features of the suspected target include thearea of the suspected target. In step 22, said acquiring the attributefeatures of the suspected target based on the plurality of frames offirst images includes, but is not limited to the following sub-steps.

In sub-step A1, a number of pixels in any frame of first image and adimension corresponding to the pixels are acquired.

For example, the terminal may acquire the pixels of each frame of firstimage and the dimension corresponding to the pixels based on the 8-bitimage data of each frame of first image.

In sub-step A2, an area of the suspected target is determined based onthe number of pixels in any frame of first image and the dimensioncorresponding to the pixels.

For example, said determining the area of the suspected target based onthe number of pixels in any frame of first image and the dimensioncorresponding to the pixels includes: for any frame of first image, aproduct of the number of pixels and the dimension corresponding to thepixels is taken as the area of the suspected target.

Optionally, the attribute features of the suspected target include theshape of the suspected target. In step 22, said acquiring the attributefeatures of the suspected target based on the plurality of frames offirst images includes, but is not limited to the following sub-steps.

In sub-step B1, boundary pixels in any frame of first image areacquired.

In sub-step B2, a shape of the suspected target is determined based onthe boundary pixels in any frame of first image.

A boundary position in any frame of first image is determined based onthe boundary pixels in any frame of first image, thereby determining theshape of the suspected target.

In step 23, the suspected target in the monitoring region is determinedas an open flame if the gray scale change features of the plurality offrames of first images and the attribute features of the suspectedtarget both satisfy an open flame condition.

The suspected target in the monitoring region is determined as an openflame if the features of a first reference number in the gray scalechange features of the first images and the features of a secondreference number in the attribute features of the suspected target bothsatisfy the open flame condition.

For example, a ratio of a first reference number to the total number ofgray scale change features of the first images reaches a firstthreshold; and a ratio of a second reference number to the total numberof attribute features of the suspected target reaches a secondthreshold. For example, if the first threshold is 90% and the secondthreshold is 85%, the first reference number is 90% of the total numberof gray scale change features of the first images, and the secondreference number is 85% of the total number of attribute features of thesuspected target. For another example, the first threshold and thesecond threshold may both be 100%, and then the first reference numberis equal to the total number of gray scale change features of the firstimages, and the second reference number is equal to the total number ofattribute features of the suspected target. That is, the suspectedtarget in the monitoring region is determined as an open flame if all ofthe gray scale change features of the first images and all of theattribute features of the suspected target satisfy the open flamecondition.

The first threshold and the second threshold may be the same ordifferent, the amplitudes of which are not limited in the embodiments ofthe present disclosure. For example, the amplitudes of the firstthreshold and the second threshold may be set based on experiences orapplication scenarios.

Optionally, the open flame condition includes, but is not limited to agray scale change curve of an open flame image and a physical attributerange of the open flame. The step 23 includes:

the suspected target in the monitoring region is determined as the openflame, if the gray scale change features of the plurality of frames offirst images accord with the gray scale change curve of the open flameimage and the attribute features of the suspected target are within thephysical attribute range.

Optionally, the gray scale change curve of the open flame image includesat least one of a time-domain change curve and a frequency-domain changecurve. The gray scale change features of the plurality of frames offirst images include at least one of change features of gray scales ofthe plurality of frames of first images in a time domain and changefeatures of gray scales of the plurality of frames of first images in afrequency domain. that the suspected target in the monitoring region isdetermined as the open flame includes:

the suspected target in the monitoring region is determined as the openflame, if the change features of the gray scales of the plurality offrames of first images in the time domain satisfy the time-domain changecurve and the attribute feature of the suspected target are within thephysical attribute range, in a case that the gray scale change featuresof the plurality of frames of first images include the change featuresof the gray scales of the plurality of frames of first images in thetime domain; and

the suspected target in the monitoring region is determined as the openflame, if the change features of the gray scales of the plurality offrames of first images in the frequency domain satisfy thefrequency-domain change curve and the attribute features of thesuspected target are within the physical attribute range, in a case thatthe gray scale change features of the plurality of frames of firstimages include the change features of the gray scales of the pluralityof frames of first images in the frequency domain; and

the suspected target in the monitoring region is determined as the openflame, if the change features of the gray scales of the plurality offrames of first images in the frequency domain satisfy thefrequency-domain change curve and the change features of the gray scalesof the plurality of frames of first images in the time domain satisfythe time-domain change curve, and the attribute feature of the suspectedtarget are within the physical attribute range, in a case that the grayscale change features of the plurality of frames of first images includethe change features of the gray scales of the plurality of frames offirst images in the frequency domain and the change features of the grayscales of the plurality of frames of first images in the time domain.

It should be noted that the time-domain change curve refers to a changecurve of the gray scale of the open flame image in the time domain, thatis, a change curve of the gray scale of the open flame image over time.That the change features of the gray scales of the plurality of framesof first images in the time domain satisfy the time-domain change curvemeans that the trend of the time-domain change curve of the gray scalesof the plurality of the first images is basically the same as that ofthe time-domain change curve of the gray scale of the open flame image.

The frequency-domain change curve refers to a change curve of the grayscale of the open flame image in the frequency domain, that is, a changecurve between the frequency of the gray scale of the open flame imageand an amplitude value of the gray scale in the frequency domain. Thatthe change features of the gray scales of the plurality of frames offirst images in the frequency domain satisfy the frequency-domain changecurve means that the trend of the frequency-domain change curve of thegray scales of the plurality of first images is basically the same asthat of the frequency-domain change curve of the gray scale of the openflame image.

The trend of the time-domain change curve of the gray scales of theplurality of frames of first images being basically the same as that ofthe time-domain change curve of the gray scale of the open flame imageincludes, but is not limited to: the similarity between the time-domainchange curve of the gray scales of the plurality of frames of firstimages and the time-domain change curve of the gray scale of the openflame image reaches a certain threshold. The trend of thefrequency-domain change curve of the gray scales of the plurality offrames of first images being basically the same as that of thefrequency-domain change curve of the gray scale of the open flame imageincludes, but is not limited to: the similarity between thefrequency-domain change curve of the gray scales of the plurality offrames of first images and the frequency-domain change curve of the grayscale of the open flame image reaches a certain threshold.

Optionally, the attribute features of the suspected target include atleast one of the followings: an area of the suspected target, a shape ofthe suspected target, a time that the suspected target stays at the sameposition, and whether the suspected target is dynamic. That thesuspected target in the monitoring region is determined as the openflame includes:

the suspected target in the monitoring region is determined as the openflame, if the attribute features of the suspected target are within acorresponding physical attribute range.

The physical property range includes an area range of the open flame, ashape of the open flame, a duration that the open flame stays at thesame position, and the open flame is dynamic.

That is, the suspected target in the monitoring region is determined asthe open flame, if at least one of the following is met: the area of thesuspected target is within an area range of the open flame, the shape ofthe suspected target matches the shape of the open flame, the time thatthe suspected target stays at the same position is within a durationthat the open flame stays at the same position, and the suspected targetis dynamic.

Therefore, the open flame is detected through the above steps 21 to 23.

Optionally, the method for detecting the open flame according to theembodiment of the present disclosure further includes:

no open flame is determined in the monitoring region, if any one of thegray scale change features of the plurality of frames of first imagesand the attribute features of the suspected target does not satisfy theopen flame condition.

It may be understood that the suspected target in the monitoring regionis not determined as the open flame, if any one of all sub-features ofthe gray scale change features of the plurality of frames of firstimages and all of the attribute features of the suspected target doesnot satisfy the open flame condition.

Optionally, the method for detecting the open flame according to theembodiment of the present disclosure further includes:

alarm information is sent out after an open flame is determined in themonitoring region in in step 23.

After determining that there is an open flame in the monitoring region,the terminal sends out the alarm information, which is conducive toprevent the open flame in time and avoid affecting the human health andcausing safety hazards.

The terminal may send out the alarm information only once, or send out aplurality of pieces of alarm information at intervals of a secondreference time. The second reference time may be 3 seconds, 5 seconds,10 seconds, 15 seconds, 20 seconds, 30 seconds, 35 seconds, 40 seconds,or the like.

The alarm information may be audio information, warning light flashing,or image display information.

According to the method for detecting the open flame provided by theembodiment of the present disclosure, the plurality of frames of firstimages of the suspected target in the monitoring region, that is, avideo of the suspected target, are acquired. It is conducive toaccurately acquire the gray scale change features of the plurality offrames of first images and the attribute features of the suspectedtarget. The temperature change features of the suspected target can beaccurately determined based on the gray scale change features of thefirst images. Two aspects (the temperature change features of thesuspected target and the attribute features of the suspected target) arecombined so as to determine whether the open flame condition issatisfied. Therefore, this method can accurately detect whether there isan open flame in the monitoring region.

Based on the same concept as the above method, as shown in FIG. 3, anembodiment of the present disclosure provides an apparatus for detectingan open flame. The apparatus includes:

a first acquiring module 31, configured to acquire a plurality of framesof first images of a suspected target in a monitoring region;

a second acquiring module 32, configured to acquire gray scale changefeatures of the plurality of frames of first images and attributefeatures of the suspected target based on the plurality of frames offirst images, the gray scale change features being configured toindicate temperature changes of the suspected target; and

a first determining module 33, configured to determine the suspectedtarget in the monitoring region as an open flame if the gray scalechange features of the plurality of frames of first images and theattribute features of the suspected target both satisfy an open flamecondition.

Optionally, the open flame condition includes a gray scale change curveof an open flame image and a physical attribute range of the open flame.The first determining module 33 is configured to:

determine the suspected target in the monitoring region as the openflame, if the gray scale change features of the plurality of frames offirst images accord with the gray scale change curve of the open flameimage and the attribute features of the suspected target are within thephysical attribute range.

Optionally, the gray scale change curve of the open flame image includesat least one of a time-domain change curve and a frequency-domain changecurve. The gray scale change features of the plurality of frames offirst image include at least one of change features of gray scales ofthe plurality of frames of first images in a time domain and changefeatures of gray scales of the plurality of frames of first images in afrequency domain. That the suspected target in the monitoring region isdetermined as the open flame includes:

the suspected target in the monitoring region is determined as the openflame, if the change features of the gray scales of the plurality offrames of first images in the time domain satisfy the time-domain changecurve and the attribute feature of the suspected target are within thephysical attribute range, in a case that the gray scale change featuresof the plurality of frames of first images include the change featuresof the gray scales of the plurality of frames of first images in thetime domain; and

the suspected target in the monitoring region is the open flame, if thechange features of the gray scales of the plurality of frames of firstimages in the frequency domain satisfy the frequency-domain change curveand the attribute features of the suspected target are within thephysical attribute range, in a case that the gray scale change featuresof the plurality of frames of first images include the change featuresof the gray scales of the plurality of frames of first images in thefrequency domain; and

the suspected target in the monitoring region is determined as the openflame, if the change features of the gray scales of the plurality offrames of first images in the frequency domain satisfy thefrequency-domain change curve and the change features of the gray scalesof the plurality of frames of first images in the time domain satisfythe time-domain change curve, and the attribute features of thesuspected target are within the physical attribute range, in a case thatthe gray scale change features of the plurality of frames of firstimages include the change features of the gray scales of the pluralityof frames of first images in the frequency domain and the changefeatures of the gray scales of the plurality of frames of first imagesin the time domain.

Optionally, the attribute features of the suspected target include atleast one of the followings: an area of the suspected target, a shape ofthe suspected target, a time that the suspected target stays at the sameposition, and whether the suspected target is dynamic. That thesuspected target in the monitoring region is determined as the openflame includes:

the suspected target in the monitoring region is determined as the openflame, if the attribute features of the suspected target is within thecorresponding physical attribute range.

The physical property range includes an area range of the open flame, ashape of the open flame, a duration that the open flame stays at thesame position, and the open flame is dynamic.

Optionally, the attribute features of the suspected target include thetime that the suspected target stays at the same position. As shown inFIG. 4, the second acquiring module 32 includes:

a first determining unit 41, configured to determine a position of thesuspected target in each frame of first image;

a first acquiring unit 42, configured to acquire at least two frames offirst images in which the suspected target has a same position, and aninterval time between two adjacent frames of first images; and

a second acquiring unit 43, configured to acquire a time that thesuspected target stays at the same position by accumulating the intervaltime between two adjacent frames of first images among the at least twoframes of first images.

Optionally, as shown in FIG. 5, the first acquiring module 31 includes:

a third acquiring unit 51, configured to acquire a plurality of framesof second images in the monitoring region, wherein a region displayed bythe second images includes a region displayed by the first images;

a first extracting unit 52, configured to acquire images of a suspectedregion by extracting a region having a gray scale value greater than agray scale threshold from the second images, wherein the suspectedtarget is located in the suspected region; and

a fourth acquiring unit 53, configured to acquire the plurality offrames of first images by extracting the images of the suspected targetfrom the plurality of frames of images of the suspected region.

Optionally, a plurality of suspected targets are located in the imagesof the suspected region. As shown in FIG. 6, the fourth acquiring unit53 includes:

a first acquiring sub-unit 61, configured to respectively acquiredistances between each suspected target and other suspected targets ineach image of the suspected region;

a second acquiring sub-unit 62, configured to acquire distance rangesbetween each open flame and other open flames in the open flame image;and

a first segmenting sub-unit 63, configured to acquire the plurality offrames of first images by segmenting a region of the suspected targetfrom each frame of image of the suspected region, if the distancesbetween each suspected target and other suspected targets in the imageof the suspected region are within the distance ranges.

Optionally, as shown in FIG. 7, the apparatus according to theembodiment of the present disclosure further includes:

a second determining module 71, configured to determine that there is noopen flame in the monitoring region, if any one of the gray scale changefeatures of the plurality of frames of first images and the attributefeatures of the suspected target does not satisfy the open flamecondition.

Optionally, as shown in FIG. 7, the apparatus according to theembodiment of the present disclosure further includes:

an alarm module 72, configured to send out alarm information after thefirst determining module determines that there is an open flame in themonitoring region.

According to the apparatus for detecting the open flame provided by theembodiment of the present disclosure, the plurality of frames of firstimages of the suspected target in the monitoring region, that is, avideo of the suspected target, is acquired by the first acquiring module31, which is conducive to accurately acquire the gray scale changefeatures of the plurality of frames of first frames and the attributefeatures of the suspected target. The temperature change features of thesuspected target can be accurately determined based on the gray scalechange features of the first images. Two aspects (the temperature changefeatures of the suspected target and the attribute features of thesuspected target) are combined so as to determine whether the open flamecondition is satisfied. Therefore, this apparatus can accurately detectwhether there is an open flame in the monitoring region.

It should be noted: when the apparatus according to the embodimentimplements its functions, only the partitioning of the above functionalmodules is used as an example. In practical applications, the foregoingfunctions can be allocated to be completed by different functionalmodules as required. That is, an internal structure of a device ispartitioned into different functional modules to complete all or part ofthe functions described above. In addition, the apparatus according tothe foregoing embodiment and the method embodiment belong to the sameconcept, and the specific implementation process is detailed in themethod embodiments, which will not be repeated here.

FIG. 8 is a schematic structural diagram of a terminal 800 for a methodfor detecting an open flame according to an embodiment of the presentdisclosure. The terminal 800 may be a portable mobile terminal, such asa smart phone, a tablet computer, a moving picture experts group audiolayer III (MP3) player, a moving picture experts group audio layer IV(MP4) player, a laptop or a desk computer. The terminal 800 may also becalled a UE (User Equipment), a portable terminal, a laptop terminal, adesk terminal, etc.

Generally, the terminal 800 includes a processor 801 and a memory 802.

The processor 801 may include one or more processing cores, such as a4-core processor and a 7-core processor. The processor 801 may beimplemented by at least one hardware of a digital signal processing(DSP), a field-programmable gate array (FPGA), and a programmable logicarray (PLA). The processor 801 may also include a main processor and acoprocessor. The main processor is a processor configured to processdata in an awake state, and is also called a central processing unit(CPU). The coprocessor is a low-power-consumption processor configuredto process the data in a standby state. In some embodiments, theprocessor 801 may be integrated with a graphics processing unit (GPU),which is configured to render and draw the content that needs to bedisplayed by a display screen. In some embodiments, the processor 801may also include an artificial intelligence (AI) processor configured toprocess computational operations related to machine learning.

The memory 802 may include one or more computer-readable storagemediums, which can be non-transitory. The memory 802 may also include ahigh-speed random access memory, as well as a non-volatile memory, suchas one or more disk storage devices and flash storage devices. In someembodiments, the non-transitory computer-readable storage medium in thememory 802 is configured to store at least one instruction, theinstruction being executed by the processor 801 to implement the methodfor detecting the open flame according to the method embodiment of thepresent disclosure.

In some embodiments, the terminal 800 also optionally includes aperipheral device interface 803 and at least one peripheral device. Theprocessor 801, the memory 802, and the peripheral device interface 803may be connected by a bus or a signal line. Each peripheral device maybe connected to the peripheral device interface 803 by a bus, a signalline or a circuit board. Specifically, the peripheral device includes atleast one of a radio frequency circuit 804, a display screen 805, acamera 806, an audio circuit 807, a positioning component 808 and apower source 809.

The peripheral device interface 803 may be configured to connect atleast one peripheral device associated with an input/output (I/O) to theprocessor 801 and the memory 802. In some embodiments, the processor801, the memory 802 and the peripheral device interface 803 areintegrated on the same chip or circuit board. In some other embodiments,any one or two of the processor 801, the memory 802 and the peripheraldevice interface 803 may be implemented on a separate chip or circuitboard, which is not limited in the present embodiment.

The radio frequency circuit 804 is configured to receive and transmit aradio frequency (RF) signal, which is also referred to as anelectromagnetic signal. The RF circuit 804 communicates with acommunication network and other communication devices via theelectromagnetic signal. The radio frequency circuit 804 converts theelectrical signal into the electromagnetic signal for transmission, orconverts the received electromagnetic signal into the electrical signal.Optionally, the RF circuit 804 includes an antenna system, an RFtransceiver, one or more amplifiers, a tuner, an oscillator, a digitalsignal processor, a codec chipset, a subscriber identity module card,and the like. The RF circuit 804 can communicate with other terminalsvia at least one wireless communication protocol. The wirelesscommunication protocol includes, but not limited to, a metropolitan areanetwork, various generations of mobile communication networks (2G, 3G,4G, and 5G), a wireless local area network, and a wireless fidelity(WiFi) network. In some embodiments, the RF circuit 804 may also includenear field communication (NFC) related circuits, which is not limited inthe present disclosure.

The display screen 805 is configured to display a user interface (UI).The UI may include graphics, text, icons, videos, and any combinationthereof. When the display screen 805 is a touch display screen, thedisplay screen 805 also has the capacity to acquire touch signals on orover the surface of the display screen 805. The touch signal may beinput into the processor 801 as a control signal for processing. At thistime, the display screen 805 may also be configured to provide virtualbuttons and/or virtual keyboards, which are also referred to as softbuttons and/or soft keyboards. In some embodiments, one display screen805 may be disposed on the front panel of the terminal 800. In someother embodiments, at least two display screens 805 may be disposedrespectively on different surfaces of the terminal 800 or in a foldeddesign. In further embodiments, the display screen 805 may be a flexibledisplay screen disposed on the curved or folded surface of the terminal800. Even the display screen 805 may have an irregular shape other thana rectangle. That is, the display screen 805 may be an irregular-shapedscreen. The display screen 805 may be prepared from a material such as aliquid crystal display (LCD), an organic light-emitting diode (OLED),etc.

The camera component 806 is configured to capture images or videos.Optionally, the camera component 806 includes a front camera and a rearcamera. Usually, the front camera is placed on the front panel of theterminal, and the rear camera is placed on the back of the terminal. Insome embodiments, at least two rear cameras are disposed, and are atleast one of a main camera, a depth-of-field camera, a wide-anglecamera, and a telephoto camera respectively, so as to realize abackground blurring function achieved by fusion of the main camera andthe depth-of-field camera, panoramic shooting and virtual reality (VR)shooting functions achieved by fusion of the main camera and thewide-angle camera or other fusion shooting functions. In someembodiments, the camera component 806 may also include a flashlight. Theflashlight may be a mono-color temperature flashlight or a two-colortemperature flashlight. The two-color temperature flash is a combinationof a warm flashlight and a cold flashlight and can be used for lightcompensation at different color temperatures.

The audio circuit 807 may include a microphone and a speaker. Themicrophone is configured to collect sound waves of users andenvironments, and convert the sound waves into electrical signals whichare input into the processor 801 for processing, or input into the RFcircuit 804 for voice communication. For the purpose of stereoacquisition or noise reduction, there may be a plurality of microphonesrespectively disposed at different locations of the terminal 800. Themicrophone may also be an array microphone or an omnidirectionalacquisition microphone. The speaker is then configured to convert theelectrical signals from the processor 801 or the RF circuit 804 into thesound waves. The speaker may be a conventional film speaker or apiezoelectric ceramic speaker. When the speaker is the piezoelectricceramic speaker, the electrical signal can be converted into not onlyhuman-audible sound waves but also the sound waves which are inaudibleto humans for the purpose of ranging and the like. In some embodiments,the audio circuit 807 may also include a headphone jack.

The positioning component 808 is configured to locate the currentgeographic location of the terminal 800 to implement navigation orlocation-based service (LBS). The positioning component 808 may be apositioning component based on the American global positioning system(GPS), the Chinese Beidou system, the Grenas system in Russia or theEuropean Union's Galileo system.

The power source 809 is configured to power up various components in theterminal 800. The power source 809 may be alternating current, directcurrent, a disposable battery, or a rechargeable battery. When the powersource 809 includes the rechargeable battery, the rechargeable batterymay a wired rechargeable battery or a wireless rechargeable battery. Therechargeable battery may also support the fast charging technology.

In some embodiments, the terminal 800 also includes one or more sensors810. The one or more sensors 810 include, but not limited to, anacceleration sensor 811, a gyro sensor 812, a pressure sensor 813, afingerprint sensor 814, an optical sensor 815 and a proximity sensor816.

The acceleration sensor 811 may detect magnitudes of accelerations onthree coordinate axes of a coordinate system established by the terminal800. For example, the acceleration sensor 811 may be configured todetect components of a gravitational acceleration on the threecoordinate axes. The processor 801 may control the display screen 805 todisplay a user interface in a landscape view or a portrait viewaccording to a gravity acceleration signal collected by the accelerationsensor 811. The acceleration sensor 811 may also be configured tocollect motion data of a game or a user.

The gyro sensor 812 can detect a body direction and a rotation angle ofthe terminal 800, and can cooperate with the acceleration sensor 811 tocollect a 3D motion of the user on the terminal 800. Based on the datacollected by the gyro sensor 812, the processor 801 can serve thefollowing functions: motion sensing (such as changing the UI accordingto a user's tilt operation), image stabilization during shooting, gamecontrol and inertial navigation.

The pressure sensor 813 may be disposed on a side frame of the terminal800 and/or a lower layer of the display screen 805. When the pressuresensor 813 is disposed on the side frame of the terminal 800, a user'sholding signal to the terminal 800 can be detected. The processor 801can perform left-right hand recognition or quick operation according tothe holding signal collected by the pressure sensor 813. When thepressure sensor 813 is disposed on the lower layer of the display screen805, the processor 801 controls an operable control on the UI accordingto a user's pressure operation on the display screen 805. The operablecontrol includes at least one of a button control, a scroll bar control,an icon control and a menu control.

The fingerprint sensor 814 is configured to collect a user'sfingerprint. The processor 801 identifies the user's identity based onthe fingerprint collected by the fingerprint sensor 814, or thefingerprint sensor 814 identifies the user's identity based on thecollected fingerprint. When the user's identity is identified astrusted, the processor 801 authorizes the user to perform relatedsensitive operations, such as unlocking the screen, viewing encryptedinformation, downloading software, paying, and changing settings. Thefingerprint sensor 814 may be provided on the front, back, or side ofthe terminal 800. When the terminal 800 is provided with a physicalbutton or a manufacturer's Logo, the fingerprint sensor 814 may beintegrated with the physical button or the manufacturer's Logo.

The optical sensor 815 is configured to collect ambient light intensity.In one embodiment, the processor 801 may control the display brightnessof the display screen 805 according to the ambient light intensitycollected by the optical sensor 815. Specifically, when the ambientlight intensity is high, the display brightness of the display screen805 is increased; and when the ambient light intensity is low, thedisplay brightness of the display screen 805 is decreased. In anotherembodiment, the processor 801 may also dynamically adjust shootingparameters of the camera component 806 based on the ambient lightintensity collected by the optical sensor 815.

The proximity sensor 816, also referred to as a distance sensor, isusually disposed on the front panel of the terminal 800. The proximitysensor 816 is configured to capture a distance between the user and afront surface of the terminal 800. In one embodiment, when the proximitysensor 816 detects that the distance between the user and the frontsurface of the terminal 800 becomes gradually smaller, the processor 801controls the display screen 805 to switch from a screen-on state to ascreen-off state. When it is detected that the distance between the userand the front surface of the terminal 800 gradually increases, theprocessor 801 controls the display screen 805 to switch from thescreen-off state to the screen-on state.

It will be understood by those skilled in the art that the structureshown in FIG. 8 does not constitute a limitation to the terminal 800,and may include more or less components than those illustrated, orcombine some components or adopt different component arrangements.

For example, a computer device is further provided. The computer deviceincludes a processor and a memory, wherein the memory is configured tostore at least one instruction. The at least one instruction isconfigured to be performed by one or more processors to implement theabove method for detecting the open flame.

For example, a computer-readable storage medium is further provided. Thecomputer-readable storage medium is configured to store at least oneinstruction therein, which is performed by the processor of the computerdevice to implement the above method for detecting the open flame.

Optionally, the computer-readable storage medium may be an ROM, a randomaccess memory (RAM), a compact disc read-only memory (CD-ROM), amagnetic tape, a floppy disk, an optical data storage device, etc.

All the above-mentioned optional technical solutions may be combined inany way to form optional embodiments of the present disclosure, whichare not be repeated here.

The foregoing descriptions are merely illustrative embodiments of thepresent disclosure, and are not intended to limit the protection scopeof the present disclosure. Within the spirit and principles of thepresent disclosure, any modifications, equivalent substitutions,improvements, etc., are within the protection scope of the presentdisclosure.

1. A method for detecting an open flame, which is applied to anelectronic device and comprises: acquiring a plurality of frames offirst images of a suspected target in a monitoring region; acquiringgray scale change features of the plurality of frames of first imagesand attribute features of the suspected target based on the plurality offrames of first images, the gray scale change features being configuredto indicate temperature changes of the suspected target; and determiningthe suspected target in the monitoring region as an open flame, inresponse to the gray scale change features of the plurality of frames offirst images and the attribute features of the suspected target bothsatisfying an open flame condition.
 2. The method according to claim 1,wherein the open flame condition comprises a gray scale change curve ofan open flame image and a physical attribute range of the open flame;and wherein said determining the suspected target in the monitoringregion as the open flame, in response to the gray scale change featuresof the plurality of frames of first images and the attribute features ofthe suspected target both satisfying the open flame condition comprises:determining the suspected target in the monitoring region as the openflame, in response to the gray scale change features of the plurality offrames of first images according with the gray scale change curve of theopen flame image and the attribute features of the suspected targetbeing within the physical attribute range.
 3. The method according toclaim 2, wherein the gray scale change curve of the open flame imagecomprises at least one of a time-domain change curve or afrequency-domain change curve; wherein the gray scale change features ofthe plurality of frames of first images comprise at least one of changefeatures of gray scales of the plurality of frames of first images in atime domain or change features of gray scales of the plurality of framesof first images in a frequency domain; and wherein said determining thesuspected target in the monitoring region as the open flame comprises:determining the suspected target in the monitoring region as the openflame, in response to the change features of the gray scales of theplurality of frames of first images in the time domain satisfying thetime-domain change curve and the attribute features of the suspectedtarget being within the physical attribute range, in a case that thegray scale change features of the plurality of frames of first imagescomprise the change features of the gray scales of the plurality offrames of first images in the time domain; determining the suspectedtarget in the monitoring region as the open flame, in response to thechange features of the gray scales of the plurality of frames of firstimages in the frequency domain satisfying the frequency-domain changecurve and the attribute feature of the suspected target being within thephysical attribute range, in a case that the gray scale change featuresof the plurality of frames of first images comprise the change featuresof the gray scales of the plurality of frames of first images in thefrequency domain; or determining the suspected target in the monitoringregion as the open flame, in response to the change features of the grayscales of the plurality of frames of first images in the frequencydomain satisfying the frequency-domain change curve and the changefeatures of the gray scales of the plurality of frames of first imagesin the time domain satisfying the time-domain change curve, and theattribute features of the suspected target being within the physicalattribute range, in a case that the gray scale change features of theplurality of frames of first images comprise the change features of thegray scales of the plurality of frames of first images in the frequencydomain and the change features of the gray scales of the plurality offrames of first images in the time domain.
 4. The method according toclaim 2, wherein the attribute features of the suspected target compriseat least one of: an area of the suspected target of the suspectedtarget, a shape of the suspected target, a time that the suspectedtarget stays at a same position, or whether the suspected target isdynamic; and wherein the physical property range comprises an area rangeof the open flame, a shape of the open flame, a duration that the openflame stays at a same position, and the open flame is dynamic.
 5. Themethod according to claim 1, wherein the attribute features of thesuspected target comprise a time that the suspected target stays at asame position, and said acquiring the attribute features of thesuspected target based on the plurality of frames of first imagescomprises: determining a position of the suspected target in each frameof first image; acquiring at least two frames of first images in whichthe suspected target has a same position, and an interval time betweentwo adjacent frames of first images among the at least two frames offirst images; and acquiring a time that the suspected target stays atthe same position by accumulating the interval time.
 6. The methodaccording to claim 1, wherein said acquiring the plurality of frames offirst images of the suspected target in the monitoring region comprises:acquiring a plurality of frames of second images in the monitoringregion, wherein a region displayed by the second images comprises aregion displayed by the first images; acquiring images of a suspectedregion by extracting a region having a gray scale value greater than agray scale threshold from the second images, wherein the suspectedtarget is located in the suspected region; and acquiring the pluralityof frames of first images by extracting the images of the suspectedtarget from a plurality of frames of images of the suspected region. 7.The method according to claim 6, wherein, based on a plurality ofsuspected targets being located in the images of the suspected region,said acquiring the plurality of frames of first images by extracting theimages of the suspected target from the plurality of frames of images ofthe suspected region comprises: acquiring distances between eachsuspected target and other suspected targets in each image of thesuspected region; acquiring distance ranges between each open flame andother open flames in the open flame image; and acquiring the pluralityof frames of first images by segmenting a region of the suspected targetfrom each frame of image of the suspected region, in response to thedistances between each suspected target and other suspected targets inthe image of the suspected region being within the distance ranges. 8.An apparatus for detecting an open flame, comprising: a first acquiringmodule, configured to acquire a plurality of frames of first images of asuspected target in a monitoring region; a second acquiring module,configured to acquire gray scale change features of the plurality offrames of first images and attribute features of the suspected targetbased on the plurality of frames of first images, the gray scale changefeatures being configured to indicate temperature changes of thesuspected target; and a first determining module, configured todetermine the suspected target in the monitoring region as an openflame, if the gray scale change features of the plurality of frames offirst images and the attribute features of the suspected target bothsatisfy an open flame condition.
 9. The apparatus according to claim 8,wherein the open flame condition comprises a gray scale change curve ofan open flame image and a physical attribute range of the open flame;and wherein the first determining module is configured to determine thesuspected target in the monitoring region as the open flame, if the grayscale change features of the plurality of frames of first images accordwith the gray scale change curve of the open flame image and theattribute features of the suspected target are within the physicalattribute range.
 10. The apparatus according to claim 9, wherein thegray scale change curve of the open flame image comprises at least oneof a time-domain change curve or a frequency-domain change curve;wherein the gray scale change features of the plurality of frames offirst image comprise at least one of change features of gray scales ofthe plurality of frames of first images in a time domain or changefeatures of gray scales of the plurality of frames of first images in afrequency domain; and wherein the first determining module is configuredto: determine the suspected target in the monitoring region as the openflame, in response to determining that the change features of the grayscales of the plurality of frames of first images in the time domainsatisfy the time-domain change curve and the attribute features of thesuspected target are within the physical attribute range, in a case thatthe gray scale change features of the plurality of frames of firstimages comprise the change features of the gray scales of the pluralityof frames of first images in the time domain; determine the suspectedtarget in the monitoring region as the open flame, in response todetermining that the change features of the gray scales of the pluralityof frames of first images in the frequency domain satisfy thefrequency-domain change curve and the attribute feature of the suspectedtarget are within the physical attribute range, in a case that the grayscale change features of the plurality of frames of first imagescomprise the change features of the gray scales of the plurality offrames of first images in the frequency domain; or determine thesuspected target in the monitoring region as the open flame, in responseto determining that the change features of the gray scales of theplurality of frames of first images in the frequency domain satisfy thefrequency-domain change curve and the change features of the gray scalesof the plurality of frames of first images in the time domain satisfythe time-domain change curve, and the attribute features of thesuspected target are within the physical attribute range, in a case thatthe gray scale change features of the plurality of frames of firstimages comprise the change features of the gray scales of the pluralityof frames of first images in the frequency domain and the changefeatures of the gray scales of the plurality of frames of first imagesin the time domain.
 11. The apparatus according to claim 9, wherein theattribute features of the suspected target comprise at least one of: anarea of the suspected target, a shape of the suspected target, a timethat the suspected target stays at a same position, or whether thesuspected target is dynamic; and wherein the physical property rangecomprises an area range of the open flame, a shape of the open flame, aduration that the open flame stays at a same position, and the openflame is dynamic.
 12. The apparatus according to claim 8, wherein theattribute features of the suspected target comprise a time that thesuspected target stays at a same position; and wherein the secondacquiring module comprises: a first determining unit, configured todetermine a position of the suspected target in each frame of firstimage; a first acquiring unit, configured to acquire at least two framesof first images in which the suspected target has a same position, andan interval time between two adjacent frames of first images among theat least two frames of first images; and a second acquiring unit,configured to acquire a time that the suspected target stays at the sameposition by accumulating the interval time.
 13. The apparatus accordingto claim 8, wherein the first acquiring module comprises: a thirdacquiring unit, configured to acquire a plurality of frames of secondimages in the monitoring region, wherein a region displayed by thesecond images includes a region displayed by the first images; a firstextracting unit, configured to acquire images of a suspected region byextracting a region having a gray scale value greater than a gray scalethreshold from the second images, wherein the suspected target islocated in the suspected region; and a fourth acquiring unit, configuredto acquire the plurality of frames of first images by extracting theimages of the suspected target from a plurality of frames of images ofthe suspected region.
 14. The apparatus according to claim 13, whereinthe plurality of suspected targets are located in the images of thesuspected region; and wherein the fourth acquiring unit comprises: afirst acquiring sub-unit, configured to acquire distances between eachsuspected target and other suspected targets in each image of thesuspected region; a second acquiring sub-unit, configured to acquiredistance ranges between each open flame and other open flames in theopen flame image; and a first segmenting sub-unit, configured to acquirethe plurality of frames of first images by segmenting a region of thesuspected target from each frame of image of the suspected region, ifthe distances between each suspected target and other suspected targetsin the image of the suspected region are within the distance ranges. 15.An apparatus for detecting an open flame, comprising a processor and amemory, wherein the memory stores at least one instruction therein, theinstruction being loaded and performed by the processor to implement themethod for detecting the open flame according to claim
 1. 16. Anon-transitory computer-readable storage medium storing at least oneinstruction therein, wherein the instruction is loaded and performed bya processor to implement the method for detecting the open flameaccording to claim
 1. 17. The method according to claim 3, wherein theattribute features of the suspected target comprise at least one of: anarea of the suspected target of the suspected target, a shape of thesuspected target, a time that the suspected target stays at a sameposition, or whether the suspected target is dynamic; and wherein thephysical property range comprises an area range of the open flame, ashape of the open flame, a duration that the open flame stays at a sameposition and the open flame is dynamic.
 18. The apparatus according toclaim 10, wherein the attribute features of the suspected targetcomprise at least one of: an area of the suspected target, a shape ofthe suspected target, a time that the suspected target stays at a sameposition, or whether the suspected target is dynamic; and wherein thephysical property range comprises an area range of the open flame, ashape of the open flame, a duration that the open flame stays at a sameposition, and the open flame is dynamic.